Computer Science > Social and Information Networks

Abstract: Opinion polarization is a ubiquitous phenomenon in opinion dynamics. In
contrast to the traditional consensus oriented group decision making (GDM)
framework, this paper proposes a framework with the co-evolution of both
opinions and relationship networks to improve the potential consensus level of
a group and help the group reach a stable state. Taking the bound of confidence
and the degree of individual's persistence into consideration, the evolution of
the opinion is driven by the relationship among the group. Meanwhile, the
antagonism or cooperation of individuals presented by the network topology also
evolve according to the dynamic opinion distances. Opinions are convergent and
the stable state will be reached in this co-evolution mechanism. We further
explored this framework through simulation experiments. The simulation results
verify the influence of the level of persistence on the time cost and indicate
the influence of group size, the initial topology of networks and the bound of
confidence on the number of opinion clusters.

Comments:

24 pages, 3 figures

Subjects:

Social and Information Networks (cs.SI); Neural and Evolutionary Computing (cs.NE)